arXiv Machine Learning By Aras Kavuncu, Bryan Vullo, Alberto Berni

Reproducing Recurrent Transformers: The CoTFormer

Read the original on arXiv Machine Learning →

arXiv:2607. 19405v1 Announce Type: new Abstract: The CoTFormer architecture formalizes Chain-of-Thought as a form of recurrent latent computation, preserving intermediate states as attendable representations to mimic explicit reasoning traces.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv AI
Jul 29

Penelope: Localized Latent Recurrence for Efficient Structured Reasoning

arXiv:2607. 25915v1 Announce Type: new Abstract: Complex structured reasoning tasks often require additional computation, yet current language models obtain it mainly by increasing parameter scale or by serializing intermediate steps as chain-of-thought (CoT) tokens.

By Yutong Chen, Shouqian Shi, Xinran Liu, Haochen Wang, Jiaying Wang, Tianxing Xu, Yuanxi Wang, Zirui Ding